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Constructing hypotheses & research design

Learn the importance of hypotheses in research, types of hypotheses, research design functions, elements of designing a research, threats to reliability and validity, and translating research questions into data. Explore various research strategies.

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Constructing hypotheses & research design

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  1. Constructing hypotheses& research design

  2. The definition of a hypothesis • A tentative proposition. • Its validity is unknown. • It specifies a relationship between two or more variables. • An answer to a research question. • It is not obligatory to have a hypothesis in a research but it is recommended.

  3. Why it is needed? • To bring direction, • specificity & • focus to a research study. • To have something to test. The hypothesis can be proved to be: • right, • partly right, • wrong (false).

  4. Functions of a hypothesis • Providing focus • What data to collect and what data not to collect • Enhancing objectivity • Making conclusions easier

  5. Types of hypothesis • Research hypothesis • Hypothesis of difference • Hypothesis of point-prevalence • Hypothesis of association • Alternate hypothesis • Null hypothesis (H0)

  6. Type I and type II errors in testing • Type I error: rejecting a hypothesis that is true • Type II error: accepting a false hypothesis

  7. Research design • The general plan of how you will go about answering your research questions: • Clear objectives derived from RQs • Identified data sources • Data collection plan • Data analysis plan • Ethical issues • Constraints

  8. Research design • Plan + Structure + Strategy of • investigation to • obtain answers to research questions or problems. • How the full research is to be completed?(operationalizing the variables, selecting the sample, data collection etc.)

  9. Functions of research design • Conceptualise an operational plan to undertake the various procedures and tasks • Ensure that the procedures will obtain valid, objective and accurate answers to teh research question.

  10. Elements of designing a research • Methodological choice: • Mono or multiple method • quantitative, qualitative or mixed methods • Recognising the purpose of design • Exploratory (what is happening, gaining insight) • Descriptive (accurate profile of sg) • Explanatory (causality) • Evaluate (how well sg works) • Combined

  11. Elements of designing a research • Choosing a research strategy: • Experiment • Survey • Archival and documentary research • Case study (!) • Action research (emergent and iterative; solutions to real problems; participative&collaborative; mixed knowledge) • Grounded theory (reality is socially constructed; developing explanations to social interactions; inductive/abductive)

  12. Elements of designing a research • Choosing a time horizon: • Cross sectional • Longitudinal • Establishing the ethics of the research • Establishing the quality of the research • Reliability • Validity • Researcher’s role: external, internal

  13. Mixed methods designs • Concurrent • Sequential: • Exploratory: (1) qualitative (2) quantitative • Explanatory: (1) quantitative (2) qualitative • Multi-phase: (1) qualitative (2) quantitative (3) qualitative

  14. Threats to reliability • Participant error: factors adversely altering the praticipants’ performance • Participant bias: inducing false response • Researcher error: factors altering the researchers’ interpretation • Researcher bias: false recording (eg. subjectivity)

  15. Threats to validity • Past or recent events changing participants’ perception • Impact of testing (being tested) • Instrumentation: change in the research instruments (e.g. definitions) during the research • Participants’ withdrawal • Maturation: change in the participants • Ambiguity of causal direction

  16. Translating research questions into data • Problem • Concepts • Research question(s), aims, hypotheses • Variables: • Dependent • Independent • Mediating: in-between, explains the relationship • Moderator: affects the relationship • Control: need to be constant • Confounding: difficult to measure, need to be considered • Planned analyzing method: level of measurement • Items in the questionnaire: understandable, fool-proof, cost-efficient • Recorded data: from the questionnaire, from other data source (eg. notes, registers, background knowledge etc.), computed variables

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